Data for Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites

Xing, X., Lu, W., Li, X., Pratas, J.S., Oschmann, A.M., Rabinowitz, J.R. June 9, 2026. Data from: “Leveraging 13C-Labeling to Assign Molecular Formulas to Unknown Yeast Metabolites.” GitHub.

Yeast Untargeted Metabolomics Peak Annotation and Analysis Pipeline tailored for unknown metabolite discovery

This repository contains the main MATLAB code pipeline for processing untargeted LC-MS metabolomics data from yeast. The pipeline includes the following steps:

Extract peak intensities across datasets.
Annotate isotopes, adducts, in-source fragment (using additional AIF data) and other redundencies.
Extract carbon information from isotopic data.
Assign molecular formulas based on carbon information.
Match formulas against HMDB/YMDB databases.
Integrate MS1 and MS2 information.
Combine all results into a structured, analysis-ready data table in “pks”

The raw mzXML data supporting this work has been deposited to Figshare and is available at:
Untargeted Metabolomics Dataset for Yeast

The file M_neg.mat contains the parsed data ready to be loaded in MATLAB. Please download and place it in the results folder before running “main.m”

GitHub: MATLAB code pipeline, raw data, results